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Huma Solana Programs - Huma Finance

Prepared by:

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HALBORN

Last Updated 12/29/2025

Date of Engagement: December 10th, 2025 - December 17th, 2025

Summary

100% of all REPORTED Findings have been addressed

All findings

2

Critical

0

High

0

Medium

0

Low

1

Informational

1

Table of Contents

1. Introduction

Huma engaged Halborn to conduct a security assessment of their Solana programs beginning on December 10, 2025, and ending on December 17, 2025. The security assessment was scoped to the Solana Programs provided in the huma-solana-programs GitHub repository. Commit hashes and further details can be found in the Scope section of this report.


The Huma programs empower liquidity providers (LPs) to participate in Huma liquidity pools and benefit from attractive yields along with $HUMA tokens as additional rewards.


This security assessment focused on the changes introduced since the previous security assessment, specifically those between commits a0b8d8e and b508edf. The main areas of change included:


    • Compatibility updates related to the Solana and Anchor version upgrade

    • Addition of the instant withdrawal feature

    • Adoption of the payer–authority pattern

    • Fixes for program panics caused by arithmetic overflows

    • Various additional fixes and improvements

2. Assessment Summary


Halborn was provided 6 days for the engagement and assigned one full-time security engineer to review the security of the Solana Programs in scope. The engineer is a blockchain and smart contract security expert with advanced smart contract hacking skills, and deep knowledge of multiple blockchain protocols.

The purpose of the assessment is to:

    • Identify potential security issues within the Solana Programs.

    • Ensure that smart contract functionality operates as intended.


In summary, Halborn identified some improvements to reduce the likelihood and impact of risks, which were partially addressed by the Huma team:

    • Correct the padding field size of the RedemptionRequest account.

    • Require the new lender to sign the transaction when creating new lender accounts.


The corresponding fix has been merged into the branches listed below, with the following commit hashes:

    • develop: 6a51d20f289857fd9bc84d32f6f33db420a17c45

    • main: 5bdb7c4884cdad1db5e97b3faee6fec4ea038ec8


3. Test Approach and Methodology

Halborn performed a combination of a manual review of the source code and automated security testing to balance efficiency, timeliness, practicality, and accuracy in regard to the scope of the program assessment. While manual testing is recommended to uncover flaws in business logic, processes, and implementation; automated testing techniques help enhance coverage of programs and can quickly identify items that do not follow security best practices.

The following phases and associated tools were used throughout the term of the assessment:

    • Research into the architecture, purpose, and use of the platform.

    • Manual program source code review to identify business logic issues.

    • Mapping out possible attack vectors

    • Thorough assessment of safety and usage of critical Rust variables and functions in scope that could lead to arithmetic vulnerabilities.

    • Scanning dependencies for known vulnerabilities (cargo audit).

    • Local runtime testing (anchor test)


4. RISK METHODOLOGY

Every vulnerability and issue observed by Halborn is ranked based on two sets of Metrics and a Severity Coefficient. This system is inspired by the industry standard Common Vulnerability Scoring System.
The two Metric sets are: Exploitability and Impact. Exploitability captures the ease and technical means by which vulnerabilities can be exploited and Impact describes the consequences of a successful exploit.
The Severity Coefficients is designed to further refine the accuracy of the ranking with two factors: Reversibility and Scope. These capture the impact of the vulnerability on the environment as well as the number of users and smart contracts affected.
The final score is a value between 0-10 rounded up to 1 decimal place and 10 corresponding to the highest security risk. This provides an objective and accurate rating of the severity of security vulnerabilities in smart contracts.
The system is designed to assist in identifying and prioritizing vulnerabilities based on their level of risk to address the most critical issues in a timely manner.

4.1 EXPLOITABILITY

Attack Origin (AO):
Captures whether the attack requires compromising a specific account.
Attack Cost (AC):
Captures the cost of exploiting the vulnerability incurred by the attacker relative to sending a single transaction on the relevant blockchain. Includes but is not limited to financial and computational cost.
Attack Complexity (AX):
Describes the conditions beyond the attacker’s control that must exist in order to exploit the vulnerability. Includes but is not limited to macro situation, available third-party liquidity and regulatory challenges.
Metrics:
EXPLOITABILITY METRIC (mem_e)METRIC VALUENUMERICAL VALUE
Attack Origin (AO)Arbitrary (AO:A)
Specific (AO:S)		1
0.2
Attack Cost (AC)Low (AC:L)
Medium (AC:M)
High (AC:H)		1
0.67
0.33
Attack Complexity (AX)Low (AX:L)
Medium (AX:M)
High (AX:H)		1
0.67
0.33
Exploitability EE is calculated using the following formula:

E=∏meE = \prod m_e

4.2 IMPACT

Confidentiality (C):
Measures the impact to the confidentiality of the information resources managed by the contract due to a successfully exploited vulnerability. Confidentiality refers to limiting access to authorized users only.
Integrity (I):
Measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of data stored and/or processed on-chain. Integrity impact directly affecting Deposit or Yield records is excluded.
Availability (A):
Measures the impact to the availability of the impacted component resulting from a successfully exploited vulnerability. This metric refers to smart contract features and functionality, not state. Availability impact directly affecting Deposit or Yield is excluded.
Deposit (D):
Measures the impact to the deposits made to the contract by either users or owners.
Yield (Y):
Measures the impact to the yield generated by the contract for either users or owners.
Metrics:
IMPACT METRIC (mIm_I)METRIC VALUENUMERICAL VALUE
Confidentiality (C)None (C:N)
Low (C:L)
Medium (C:M)
High (C:H)
Critical (C:C)		0
0.25
0.5
0.75
1
Integrity (I)None (I:N)
Low (I:L)
Medium (I:M)
High (I:H)
Critical (I:C)		0
0.25
0.5
0.75
1
Availability (A)None (A:N)
Low (A:L)
Medium (A:M)
High (A:H)
Critical (A:C)		0
0.25
0.5
0.75
1
Deposit (D)None (D:N)
Low (D:L)
Medium (D:M)
High (D:H)
Critical (D:C)		0
0.25
0.5
0.75
1
Yield (Y)None (Y:N)
Low (Y:L)
Medium (Y:M)
High (Y:H)
Critical (Y:C)		0
0.25
0.5
0.75
1
Impact II is calculated using the following formula:

I=max(mI)+∑mI−max(mI)4I = max(m_I) + \frac{\sum{m_I} - max(m_I)}{4}

4.3 SEVERITY COEFFICIENT

Reversibility (R):
Describes the share of the exploited vulnerability effects that can be reversed. For upgradeable contracts, assume the contract private key is available.
Scope (S):
Captures whether a vulnerability in one vulnerable contract impacts resources in other contracts.
Metrics:
SEVERITY COEFFICIENT (CC)COEFFICIENT VALUENUMERICAL VALUE
Reversibility (rr)None (R:N)
Partial (R:P)
Full (R:F)		1
0.5
0.25
Scope (ss)Changed (S:C)
Unchanged (S:U)		1.25
1
Severity Coefficient CC is obtained by the following product:

C=rsC = rs

The Vulnerability Severity Score SS is obtained by:

S=min(10,EIC∗10)S = min(10, EIC * 10)

The score is rounded up to 1 decimal places.
SeverityScore Value Range
Critical9 - 10
High7 - 8.9
Medium4.5 - 6.9
Low2 - 4.4
Informational0 - 1.9

5. SCOPE

REPOSITORY
(a) Repository: huma-solana-programs
(b) Assessed Commit ID: b508edf
(c) Items in scope:
  • programs/huma/src/common/huma_config/instructions/create_huma_config.rs
  • programs/huma/src/common/huma_config/instructions/liquidity_asset.rs
  • programs/huma/src/common/huma_config/instructions/pause.rs
↓ Expand ↓
Out-of-Scope: Third party dependencies and economic attacks.
Remediation Commit ID:
Out-of-Scope: New features/implementations after the remediation commit IDs.

6. Assessment Summary & Findings Overview

Critical

0

High

0

Medium

0

Low

1

Informational

1

Security analysisRisk levelRemediation Date
Incorrect padding adjustment after RedemptionRequest struct updateLowSolved - 12/17/2025
Risk of denial of service after adding new lendersInformationalAcknowledged - 12/18/2025

7. Findings & Tech Details

7.1 Incorrect padding adjustment after RedemptionRequest struct update

//

Low

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash
https://github.com/00labs/huma-solana-programs/pull/321

7.2 Risk of denial of service after adding new lenders

//

Informational

Description
BVSS
Recommendation
Remediation Comment

8. Automated Testing

Halborn strongly recommends conducting a follow-up assessment of the project either within six months or immediately following any material changes to the codebase, whichever comes first. This approach is crucial for maintaining the project’s integrity and addressing potential vulnerabilities introduced by code modifications.

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Huma Solana Programs

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